AI Learning Systems Engineer

About This Opportunity

We are representing a confidential technology consulting organization seeking an AI Learning Systems Engineer to join their team on a remote basis across the United States. This role focuses on designing, training, and deploying reinforcement learning systems for complex decision-making applications where traditional supervised learning approaches fall short.

Our client values both research depth and engineering pragmatism, seeking candidates who can bridge the gap between experimental RL work and production-grade systems that prioritize stability, safety, and continuous improvement.

Responsibilities

• Design and implement reinforcement learning-based systems for high-impact decision-making problems
• Train and deploy RL policies at scale using modern deep learning frameworks
• Build and maintain simulation environments for large-scale experience collection
• Design and tune reward functions for non-trivial problem domains
• Train neural network policies on GPU clusters with attention to computational efficiency
• Evaluate policy performance with rigorous testing and monitoring frameworks
• Collaborate with cross-functional teams to transition RL solutions from research to production
• Document technical approaches and communicate findings to both technical and non-technical stakeholders

What We're Looking For

Required Qualifications:

• Master's or PhD in Computer Science, Machine Learning, or related field; or equivalent applied experience
• 6+ years of combined reinforcement learning research and engineering experience
• Strong proficiency in Python and modern deep learning frameworks
• Hands-on experience with at least one major RL library or custom RL stack
• Solid understanding of probability, optimization, and theoretical foundations of RL
• Demonstrated experience designing and tuning reward functions in complex environments
• Experience with simulation environments and large-scale data collection
• Track record of training neural network policies on GPU infrastructure
• Strong written and verbal communication skills
• Proven history of shipping or publishing impactful RL work
• Must be a U.S. Citizen, Green Card Holder, EAD Holder, or H-1B transfer candidate (new H-1B sponsorship not available)

Preferred Qualifications:

• Experience with RLHF (Reinforcement Learning from Human Feedback) for large language models
• Familiarity with multi-agent RL or hierarchical RL approaches
• Background in robotics, control systems, or autonomous driving
• Publications in RL or related research venues
• Open-source contributions to RL libraries or simulation environments

How We Work With You

Get A Job.ai represents this employer in our capacity as a recruiting partner. When you apply through our platform at getajob.ai, our talent team will review your qualifications and conduct an initial screening. Qualified candidates will then be submitted directly to our client for consideration. Please do not attempt to contact the employer directly, as all applications must come through Get A Job.ai to be considered for this confidential search.

Pay

This is a full-time, direct W2 position that is 100% remote within the United States. While our client offers competitive compensation, specific pay details will be discussed during the screening process with our recruiting team.

Equal Employment Opportunity
Get A Job.ai is committed to equal employment opportunity. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We evaluate all candidates based on qualifications and merit.